Vendors are Undermining the Structure of U.S. Elections

As we approach the 2008 general election, the structure of elections in the United States -- once reliant on local representatives accountable to the public -- has become almost wholly dependent on large corporations, which are not accountable to the public. Most local officials charged with running elections are now unable to administer elections without the equipment, services, and trade-secret software of a small number of corporations. If the vendors withdrew their support for elections now, our election structure would collapse. Case studies presented in this report give examples of the pervasive control voting system vendors now have over election administration in almost every state, and the consequences some jurisdictions are already experiencing.However, some states and localities are recognizing the threat that vendor-dependency poses to elections. They are using ingenuity and determination to begin reversing the direction. This report examines the situation, how we got here, and steps we can take to limit corporate control of our elections in 2008 and reduce it even further in the future

A survey of the machine interference problem

This paper surveys the research published on the machine interference problem since the 1985 review by Stecke & Aronson. After introducing the basic model, we discuss the literature along several dimensions. We then note how research has evolved since the 1985 review, including a trend towards the modelling of stochastic (rather than deterministic) systems and the corresponding use of more advanced queuing methods for analysis. We conclude with some suggestions for areas holding particular promise for future studies.Natural Sciences and Engineering Research Council (NSERC) Discovery Grant 238294-200

Distributed computation of transient state distributions and passage time quantiles in large semi-Markov models

Submitted versio

Performance queries on Semi-Markov Stochastic Petri nets with an extended continuous Stochastic logic

Semi-Markov Stochastic Petri Nets (SM-SPNs) are a highlevel formalism for defining semi-Markov processes. We present an extended Continuous Stochastic Logic (eCSL) which provides an expressive way to articulate performance queries at the SM-SPN model level. eCSL supports queries involving steady-state, transient and passage time measures. We demonstrate this by formulating and answering eCSL queries on an SM-SPN model of a distributed voting system with up to ¢¤£¦ ¥ states.

On dynamic resource allocation in systems with bursty sources

There is a trend to use computing resources in a way that is more removed from the technical constraints. Users buy compute time on machines that they do not control or necessarily know the specifics of. Conversely this means the providers of such resources have more freedom in allocating them amongst different tasks. They can use this freedom to provide more, or better, service by reallocating resources as demand for them changes. However deciding when to reallocate resources is not trivial. In order to make good reallocation decisions, this thesis constructs a series of models. Each of the models concerns a resource allocation problem in the presence of bursty sources. The focus of the modelling, however, varies. In its most basic form it considers several different job types competing over the allocation of a limited number of servers. The goal there is to minimize the (weighted) mean time jobs spend in the system. The weighting can reflect the relative importance of the different job types. Reallocation of servers between job types is in general considered to be neither free nor instantaneous. We then show how to find the optimal static allocation of servers over job types. Finding the optimal dynamic allocation of servers is formulated as solving a Markov decision process. We show that this is practically unfeasible for all but the most simple systems. Instead a number of heuristics are introduced. Some are fluid-approximation based and some are parameterless, i.e. do not require the a priori knowledge of parameters of the system. The performance of these heuristic policies is then explored in a series of simulations. A slightly different model is formulated next. Its goal is not to optimize allocation of servers over several job types, but rather between powered up and powered down states. In the powered up state servers can provide service for incoming jobs. In the powered down state servers cannot service incoming jobs but incur a profit due to power savings. Balancing power and performance is again formulated as a Markov decision process. This is not explicitly solved but instead some of the heuristics considered earlier are adapted to give dynamic policies for powering servers up and v down. Their performance is again tested in a number of simulations, including some where the arrival process is not only bursty but also non-Markovian. The third and final model considers allocation of servers over different job types again. This time the servers experience breakdowns and subsequent repairs. During a repair period the servers cannot process any incoming jobs. To reduce the complexity of this model, it is assumed that switches of servers between job types are instantaneous, albeit not necessarily free. This is modeled as a Markov decision process and we show how to find the optimal static allocation of servers. For the dynamic allocation previously considered heuristics are adapted again. Simulations then show the performance of these heuristics and the optimal static allocation in a number of scenarios.EThOS - Electronic Theses Online ServiceGBUnited Kingdo